Automated‑ML automates training and evaluating machine learning models on tabular data with minimal setup.

Automated end-to-end MLOps pipeline for predicting customer purchase likelihood of a wellness tourism package, enabling data-driven marketing through CI/CD-enabled model training and deployment.

My first startup failed after corporate life... still best decision I ever made (I will not promote)

Wine Quality Prediction Classification Dataset

Predict whether a news article is real or fake.

Predict Student academic performancebased on demographic and school factors

Iris Flower Species Classification Dataset

Anomaly detection system for security risk identification in audit logs using Isolation Forest algorithm. Features automated CI/CD ML workflows with Azure DevOps for continuous model deployment and real-time alerting capabilities.

Spine surgery has massive decision variability. Retrospective ML won’t fix it. Curious if a workflow-native, outcome-driven approach could. [D]

Neural Architecture Search using Differential Evolution

Classify wine quality from physicochemical properties

Classify customer churn (yes/no) from usage and account features (classification).

[D] Why Causality Matters for Production ML: Moving Beyond Correlation

Classify emails as spam or not spam using NLP techniques

Test Final Improvements Classification

Titanic Machine Learning from Disaster Survival Prediction Dataset

Nvidia: End-to-End Test-Time Training for Long Context aka Being Able To Update A Model's Weights In Real-Time As You Use It | "TTT changes the paradigm from re

A simple explanation of Naive Bayes Classification

Final Test Complete System

Predict customer churn based on purchase history